domains Module

The domains module provides functions for curvature-based segmentation of meshes into domains and subsequent domain merging and analysis.

Domain Segmentation

steepest_ascent(mesh, scalars, neighbours=None)[source]

Create domains using steepest ascent approach.

Connects vertices based on the steepest local gradient in the scalar field.

Parameters:
Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of domain labels with length mesh.n_points

Raises:

RuntimeError – If scalar array has invalid dimensions

Domain Merging

merge_small(mesh, domains, threshold, metric='points', mode='border', neighbours=None)[source]

Merge domains smaller than threshold to their largest neighbor.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of domain labels

  • threshold (float) – Size threshold below which domains are merged

  • metric (str, default: 'points') – Size metric to use for merging (‘points’ or ‘area’)

  • mode (str, default: 'border') – Merge strategy (‘border’ or ‘area’)

  • neighbours (list[ndarray[tuple[Any, ...], dtype[int64]]] | None, default: None) – Optional neighbor connectivity array

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

Raises:

RuntimeError – If domains array is invalid

merge_angles(mesh, domains, meristem_index, threshold=20, method='center_of_mass')[source]

Merge domains based on angular separation from meristem.

Merges domains that are within the angular threshold when measured from the meristem center.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of current domain labels

  • meristem_index (int) – Index of the meristem domain

  • threshold (float, default: 20) – Angular threshold in degrees for merging domains

  • method (str, default: 'center_of_mass') – Method for calculating domain center coordinates

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

merge_distance(mesh, domains, threshold, scalars=None, method='center_of_mass', metric='euclidean')[source]

Merge domains based on spatial distance between domain centers.

Uses KDTree to find domains within the distance threshold.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of current domain labels

  • threshold (float) – Distance threshold for merging domains

  • scalars (ndarray[tuple[Any, ...], dtype[floating[Any]]] | None, default: None) – Optional scalar array for distance calculation

  • method (str, default: 'center_of_mass') – Method for calculating domain center

  • metric (str, default: 'euclidean') – Distance metric (‘euclidean’ or ‘geodesic’)

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

Raises:

RuntimeError – If method or metric is invalid

merge_engulfing(mesh, domains, threshold=0.9, neighbours=None)[source]

Merge domains that are mostly encircled by a neighboring domain.

Merges domains where a single neighbor borders more than the threshold fraction of the domain boundary.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of domain labels

  • threshold (float, default: 0.9) – Fraction of boundary that must be shared for merging

  • neighbours (list[ndarray[tuple[Any, ...], dtype[int64]]] | None, default: None) – Optional neighbor connectivity array

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

Raises:

RuntimeError – If domains array is invalid

merge_disconnected(mesh, domains, meristem_index, threshold, neighbours=None)[source]

Merge domains disconnected from meristem to nearest connected domain.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of domain labels

  • meristem_index (int) – Index of the meristem domain

  • threshold (float | None) – Distance threshold; if None, returns domains unchanged

  • neighbours (list[ndarray[tuple[Any, ...], dtype[int64]]] | None, default: None) – Optional neighbor connectivity array

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

Raises:

RuntimeError – If domains array is invalid

merge_depth(mesh, domains, scalars, threshold=0.0, neighbours=None, exclude_boundary=False, min_points=0, mode='max')[source]

Merge domains based on depth similarity in scalar field.

Merges neighboring domains if their depth values differ by less than threshold.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of domain labels

  • scalars (ndarray[tuple[Any, ...], dtype[floating[Any]]]) – Scalar array representing depth or curvature values

  • threshold (float, default: 0.0) – Maximum depth difference for merging

  • neighbours (list[ndarray[tuple[Any, ...], dtype[int64]]] | None, default: None) – Optional neighbor connectivity array

  • exclude_boundary (bool, default: False) – Exclude boundary vertices from depth calculation

  • min_points (int, default: 0) – Minimum number of border points required for merging

  • mode (Literal['min', 'max', 'median', 'mean'], default: 'max') – Aggregation mode for domain depth (‘min’, ‘max’, ‘median’, ‘mean’)

Return type:

ndarray[tuple[Any, ...], dtype[integer[Any]]]

Returns:

Array of merged domain labels

Raises:

RuntimeError – If domains or scalars arrays are invalid

Domain Analysis

define_meristem(mesh, domains, method='center_of_mass', return_coordinates=False, neighbors=None)[source]

Identify which domain corresponds to the meristem.

Parameters:

  • mesh (PolyData) – PyVista mesh containing the domains

  • domains (ndarray[tuple[Any, ...], dtype[integer[Any]]]) – Array of domain labels

  • method (str, default: 'center_of_mass') – Method for meristem identification

  • return_coordinates (bool, default: False) – If True, return meristem center coordinates

  • neighbors (list[ndarray[tuple[Any, ...], dtype[int64]]] | None, default: None) – Optional neighbor connectivity array

Return type:

int | tuple[int, ndarray[tuple[Any, ...], dtype[floating[Any]]]]

Returns:

Meristem domain index, and optionally its center coordinates

extract_domaindata(point_data, mesh, apex, meristem)

Extract geometric and spatial data for each domain.

Computes distance to boundary, distance to center of mass, angle from apex, surface area, maximum diameter, and meristem flag for each domain.

Parameters:

  • point_data (DataFrame) – DataFrame with domain labels in ‘domain’ column

  • mesh (PolyData) – PyVista mesh containing the domains

  • apex (ndarray[tuple[Any, ...], dtype[floating[Any]]]) – Apex coordinates as 3-element array

  • meristem (int) – Meristem domain index

Return type:

DataFrame

Returns:

DataFrame with domain measurements and properties

Scalar Filtering

median(scalars, neighbors=None, iterations=1)[source]

Apply median filter to mesh-based scalar arrays.

Parameters:
Return type:

ndarray[tuple[Any, ...], dtype[floating[Any]]]

Returns:

Filtered scalar array

mean(scalars, neighbors, iterations=1, exclude=None)[source]

Apply mean filter to scalar array.

Parameters:
Return type:

ndarray[tuple[Any, ...], dtype[floating[Any]]]

Returns:

Filtered scalar array

minmax(scalars, neighbors=None, iterations=1)[source]

Apply min-max filter to mesh-based scalar arrays.

Parameters:
Return type:

ndarray[tuple[Any, ...], dtype[floating[Any]]]

Returns:

Filtered scalar array

maxmin(scalars, neighbors=None, iterations=1)[source]

Apply max-min filter to mesh-based scalar arrays.

Parameters:
Return type:

ndarray[tuple[Any, ...], dtype[floating[Any]]]

Returns:

Filtered scalar array